def process_sentence(sentence):
print sentence.text.encode('utf-8')
_, frametext, reltext, matches = pattern_parse(sentence.text)
if reltext is None or reltext == 'junk': return []
else:
return [dict(id=sentence.id, frametext=frametext, reltext=reltext,
matches=matches)]
def process_sentence(sentence):
print sentence.text.encode('utf-8')
_, frametext, reltext, matches = pattern_parse(sentence.text)
if reltext is None or reltext == 'junk': return []
else:
return [
dict(id=sentence.id,
frametext=frametext,
reltext=reltext,
matches=matches)
]
def process_sentence(sentence, lang, batch):
print sentence.text.encode('utf-8')
_, frametext, reltext, matches = pattern_parse(sentence.text)
if reltext is None or reltext == 'junk': return []
relation = Relation.objects.get(name=reltext)
text_factors = [lang.nl.lemma_factor(matches[i]) for i in (1, 2)]
concepts = [Concept.objects.get_or_create(language=lang, text=stem)[0]
for stem, residue in text_factors]
for c in concepts: c.save()
surface_forms = [SurfaceForm.objects.get_or_create(concept=concepts[i],
text=matches[i+1],
residue=text_factors[i][1],
language=lang)[0]
for i in (0, 1)]
for s in surface_forms: s.save()
freq, _ = Frequency.objects.get_or_create(text=matches.get('a', ''),
language=lang,
defaults=dict(value=50))
freq.save()
frame, _ = Frame.objects.get_or_create(relation=relation, language=lang,
text=frametext, frequency=freq,
defaults=dict(goodness=1))
frame.save()
raw_assertion, _ = RawAssertion.objects.get_or_create(
surface1=surface_forms[0],
surface2=surface_forms[1],
frame=frame,
language=lang,
defaults=dict(batch=batch))
# still need to set assertion_id
assertion, _ = Assertion.objects.get_or_create(
relation=relation,
concept1=concepts[0],
concept2=concepts[1],
frequency=freq,
language=lang,
defaults=dict(score=0)
)
assertion.score += 1
assertion.save()
raw_assertion.assertion = assertion
raw_assertion.save()
rating1, _ = Rating.objects.get_or_create(
user=sentence.creator, activity=csamoa4_activity,
sentence=sentence, score=1
)
rating2, _ = Rating.objects.get_or_create(
user=sentence.creator, activity=csamoa4_activity,
raw_assertion=raw_assertion, score=1
)
rating1.save()
rating2.save()
print '=>', str(assertion).encode('utf-8')
return [assertion]
def process_sentence(sentence, lang, batch):
print sentence.text.encode('utf-8')
_, frametext, reltext, matches = pattern_parse(sentence.text)
if reltext is None or reltext == 'junk': return []
relation = Relation.objects.get(name=reltext)
text_factors = [lang.nl.lemma_factor(matches[i]) for i in (1, 2)]
concepts = [
Concept.objects.get_or_create(language=lang, text=stem)[0]
for stem, residue in text_factors
]
for c in concepts:
c.save()
surface_forms = [
SurfaceForm.objects.get_or_create(concept=concepts[i],
text=matches[i + 1],
residue=text_factors[i][1],
language=lang)[0] for i in (0, 1)
]
for s in surface_forms:
s.save()
freq, _ = Frequency.objects.get_or_create(text=matches.get('a', ''),
language=lang,
defaults=dict(value=50))
freq.save()
frame, _ = Frame.objects.get_or_create(relation=relation,
language=lang,
text=frametext,
frequency=freq,
defaults=dict(goodness=1))
frame.save()
raw_assertion, _ = RawAssertion.objects.get_or_create(
surface1=surface_forms[0],
surface2=surface_forms[1],
frame=frame,
language=lang,
defaults=dict(batch=batch))
# still need to set assertion_id
assertion, _ = Assertion.objects.get_or_create(relation=relation,
concept1=concepts[0],
concept2=concepts[1],
frequency=freq,
language=lang,
defaults=dict(score=0))
assertion.score += 1
assertion.save()
raw_assertion.assertion = assertion
raw_assertion.save()
rating1, _ = Rating.objects.get_or_create(user=sentence.creator,
activity=csamoa4_activity,
sentence=sentence,
score=1)
rating2, _ = Rating.objects.get_or_create(user=sentence.creator,
activity=csamoa4_activity,
raw_assertion=raw_assertion,
score=1)
rating1.save()
rating2.save()
print '=>', str(assertion).encode('utf-8')
return [assertion]
